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AI for Beginners - SWFLN Makerpalooza - Session 1

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AI for Beginners - SWFLN Makerpalooza - Session 1

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This session explores what artificial intelligence (AI) is and the everyday use cases for AI. It’s an introductory look at how various industries, including libraries, use AI for operational efficiencies, enhanced services, and more.

This session explores what artificial intelligence (AI) is and the everyday use cases for AI. It’s an introductory look at how various industries, including libraries, use AI for operational efficiencies, enhanced services, and more.


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AI for Beginners - SWFLN Makerpalooza - Session 1

  1. 1. AI For Beginners Brian Pichman Evolve Project @Bpichman Mastadon: https://libraryland.social
  2. 2. Evolve Project | Brian Pichman 2 AI: The Good, The Bad, The Ugly This session explores what artificial intelligence (AI) is and the everyday use cases for AI. It’s an introductory look at how various industries, including libraries, use AI for operational efficiencies, enhanced services, and more. Today we are exploring… Welcome
  3. 3. What is Artificial Intelligence the theory and development of computer systems able to perform tasks that normally require human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages.
  4. 4. What is Machine Learning Machine Learning is a subset of Artificial Intelligence that uses algorithms and statistical models to allow a computer system to make decisions around a specific task without explicit instructions; relying on patterns and inference
  5. 5. Evolve Project | Brian Pichman 5 When talking about AI… People will have one of two reactions:
  6. 6. Evolve Project | Brian Pichman 6 “The Agenda” Topics for Today AI As A Tool When introducing AI to the its best to explain what it is…and what it isn’t. Impacts to Industries How are we seeing AI Impact different industries now? Pulling it Together How can we embrace AI and move things forward? Using AI Many of us interact regularly with some variant of Artificial Intelligence.
  7. 7. Evolve Project | Brian Pichman 7 AI is becoming more available to the masses; being incorporated into our smart phones, our connected homes, and simple robots we already use today such as Roomba. With more accessible cloud- computing, open source, and the making community, this field will rapidly expand. More Widely Available Using AI “The development of full artificial intelligence could spell the end of the human race….It would take off on its own, and re-design itself at an ever increasing rate. Humans, who are limited by slow biological evolution, couldn't compete, and would be superseded.”— Stephen Hawking
  8. 8. Evolve Project | Brian Pichman 8 What makes up an intelligent system? AI Components Logic and Rules Based Computer makes decisions based on a decision tree, logic rules, or a predefined process with a calculated result. Pattern Based (Machine Learning) Computer learns overtime by using data and algorithms to detect patterns. Deep Learning Deep Learning is a subset of Machine Learning that enables the computer to make decisions on its own. Neural Networks A neural network allows an AI to make its own conclusions, where a simple pattern-only based AI must rely solely on data. A neural network allows deep learning to function.
  9. 9. Pattern Based Intelligence -> currently exists with self driving cars, language translations, movie recommendations etc. Strong Artificial Intelligence -> (doesn’t yet exist) • computers think at a level that meets or passes people (abstract thinking) Artificial Intelligence Exists
  10. 10. Evolve Project | Brian Pichman 10 Flash Light Examples Understanding AI If an ML algorithm makes an inaccurate prediction, then the engineer needs to correct. In DL, the algorithms can determine on their own if a prediction is accurate or not. Deep Learning Allow machines to make to their own accurate decisions without intervention from engineer Neural Networks If detects {dark} turn on {light} Logic Rules it’s performing a function with the data given and gets progressively better at that function Machine Learning Eventually, the system can turn on the light with other queues such as “I can’t see” DL “Code” Flashlight will turn on automatically as it learns other words for “dark” picking up on phrases that contains the word ML “Code”:
  11. 11. Evolve Project | Brian Pichman 11 create an algorithm that is able to teach itself without any external help Pattern Recognition Deep Learning Uses more complicated mathematical models to define pictures content and speech Self Learning The advance machine learning system makes decisions by analyzing its own data and making patterns Learning on Examples This method is used when a machine learns through examples. For instance, Google’s automatic spam filtering learns as users report spam. Learning on Experience The system learns from positive and negative experiences.
  12. 12. 13 From Patterns to Automation AI Models The idea is that an algorithm will sift through the data, learn from it, and apply it to make a decision. This can be seen in any recommendation type service. Machine Learning takes it a step farther by automating tasks; helping data security firms identify potential threats or finance looking for favorable deals. AI’s can be Transactional in which a question is asked and an answer is given, like a virtual assistant. AI’s can also be Automated in which routine tasks such automatically taking trash out on garbage day.
  13. 13. Evolve Project | Brian Pichman 14 • When editing or using filters in photos (do X to eyes and Y to ears) • Identification of license plates from an image in a toll violation • Facebook’s ability to identify and recommend faces in photos • iPhone users can have their phone categorize people by facial patterns – in which you then define their name • Google’s Image Recognition Examples How we see AI In Everyday Life Image Recognition Think of how we can use facial imaging to determine moods
  14. 14. Evolve Project | Brian Pichman 16 You probably see this everyday if you use Siri, Google Home, or an Echo Product. Overtime or with training, a system can tailored results based on identifying the user asking. For example, Google Home will provide my personal driving times to work if it hears me ask “how long will it take me to get to work” versus a friend asking who it has no data on. Examples How we see AI In Everyday Life Voice Recognition Think of how a system can respond and remember a user based solely on their voice
  15. 15. Evolve Project | Brian Pichman 19 Helpful – AI
  16. 16. Evolve Project | Brian Pichman 21 And How We Use It Other Forms of AI Optical Character Recognition Think of how a picture of your license plate allows a machine to translate that to text and run a query to determine who violated a toll. Also see this in scanners that can take an image and convert this to text. Consider how you can take a photo of another language and have it translate to yours Advance User Preferences This is the concept of an AI providing solutions based on historic user’s preferences and comparing it to similar users. Compare how Amazon or Netflix makes recommendations based on your purchases or views – or even how Amazon guesses when you might run out of a specific product. Sensory Data Analysis Your wearables that detect heart rate for instance can determine without user intervention if you are working out and even what kind of work out such as jogging or bicycling.
  17. 17. Healthcare Used in healthcare to identify and notice predictable trends – such as having a machine look at charts to recognize tumors sooner with more accuracy – or eyes to determine stage of glaucoma
  18. 18. Evolve Project | Brian Pichman 26 Good Read: https://www.businessinsider.com/healthcare-artificial-intelligence-pitfalls-2019-3
  19. 19. Smart Homes See how a home can alert when it sees a person versus an animal or know that its going to rain tomorrow so no need to water the grass today
  20. 20. Service Industries AI has the potential to replace many minimum wage jobs
  21. 21. https://www.bbc.com/news/av/technology-43292047/burger-flipping-robot-begins-first-shift
  22. 22. Autonomous Driving Autonomous driving Level 4 describes vehicles that can operate without human interaction in most, but not all, conditions and locations and will likely operate in geofenced areas. Autonomous driving Level 5 labels vehicles operating autonomously in all situations and conditions, and controlling all tasks.
  23. 23. Evolve Project | Brian Pichman 35 Inspiring AI’s AI: AlphaGo AlphaGo is the first AI to beat a human in arguably the most difficult game to master. AlphaGo now teaches moves to trainees. AI: ROSS ROSS is an AI tool to make legal research easier and faster
  24. 24. Evolve Project | Brian Pichman 37 Run-away AI’s Tay (Thinking About You) Released on March 23 2016 via Twitter, Tay (as TayTweets on Twitter) was designed to mimic the interactions of 19 year old girl through learned conversations on Twitter. Users began tweeting pollitcally incorrect phrases to Tay, and thus, Tay responded and answered with the learned inappropriate behavior – as it was it was not taught what the difference between Good Language and Bad Language was. Microsoft Artificial Chatter Bot
  25. 25. Evolve Project | Brian Pichman 38 Run-away AI’s Inspirobot.me I am an artificial intelligence dedicated to generating unlimited amounts of unique inspirational quotes for endless enrichment of pointless human existence. -- From their website Happy Accidents
  26. 26. Evolve Project | Brian Pichman 39 Logic and Rules Based Challenges for AI Training Similar to having good data, an AI might need to learn the correct response for the correct situation or identify dangers or inappropriate interactions Precision The idea of garbage data in garbage data out. If you flood an AI with bad data and don’t set the proper syntax or thresholds you will get incoherent results Context AI’s can struggle with understanding context. For example, asking Siri ”call me an ambulance” may yield “OK, from now on, I will call you Ambulance”
  27. 27. Evolve Project | Brian Pichman 40 Things to Expand Your Knowledge Cool Resources to Check Out IBM Watson Watson was created as a question answering (QA) computing system that IBM built to apply advanced natural language processing, information retrieval, knowledge representation, automated reasoning, and machine learning technologies to the field of open domain question answering. – Wikipedia Powered by the latest innovations in machine learning, Watson lets you learn more with less data. You can integrate AI into your most important business processes, informed by IBM’s rich industry expertise. You can build models from scratch, or leverage our APIs and pre-trained business solutions. No matter how you use Watson, your data and insights belong to you − and only you. --IBM Watson
  28. 28. By Pgr94 - Own work based on diagram found at http://www.aaai.org/Magazine/Watson/watson.php, CC0, https://commons.wikimedia.org/w/index.php?curid=14575947
  29. 29. Evolve Project | Brian Pichman 42 Things to Expand Your Knowledge Cool Resources to Check Out Kaggle Kaggle is an online community of data scientists and machine learners, owned by Google, Inc. Kaggle allows users to find and publish data sets, explore and build models in a web-based data-science environment, work with other data scientists and machine learning engineers, and enter competitions to solve data science challenges. Kaggle got its start by offering machine learning competitions and now also offers a public data platform, a cloud-based workbench for data science, and short form AI education. -- Wikipedia
  30. 30. Evolve Project | Brian Pichman 44 Things to Expand Your Knowledge Cool Resources to Check Out TensorFlow TensorFlow is an open-source software library for dataflow programming across a range of tasks. It is a symbolic math library, and is also used for machine learning applications such as neural networks. It is used for both research and production at Google. TensorFlow was developed by the Google Brain team for internal Google use. It was released under the Apache 2.0 open-source license on November 9, 2015. -- Wikipedia
  31. 31. Evolve Project | Brian Pichman 46 Books written by an AI https://link.springer.com/book/10.1007/978-3-030-16800-1
  32. 32. Evolve Project | Brian Pichman 47 AI Games AI Image or Not: http://www.whichfaceisreal.com/ https://experiments.withgoogle.com/collection/ai
  33. 33. Evolve Project | Brian Pichman 48 AI Content Creation Tools Learn more about these in the other sessions today!
  34. 34. Evolve Project | Brian Pichman 49 Activity https://affinelayer.com/pixsrv/
  35. 35. Evolve Project | Brian Pichman 50 Feel free to reach out! Questions / Contacts 815-534-0403 www.evolveproject.org bpichman@evolveproject.org Twitter: @bpichman linkedin.com/in/bpichman slideshare.net/bpichman

Hinweis der Redaktion

  • AI comes in three main forms:
    human-like interactions (agents, chatbots, robots),
    insight generation and
    advanced automation.

    Success with AI won’t mainly come from a small number of experts thinking hard in a back room; it will come from democratizing AI — getting everyone in your organization playing with all the very friendly, easy-to-use AI tools that are out there.

    Autonomous things exist across five types:
  • which comes in a variety of types such as Care Bot that can measure blood pressure, heart rate, remind users to take medicine, and even support video calls when there is an emergency. Or the Samsung Bot Retail which in a library setting can potentially guide users to find the items they need through facial and object recognition. It can even deliver items to the user!
  • The concept of autonomous flying vehicles isn’t just for human passengers but can be applied to transport many other things such as medical supplies, packages, food delivery and more. Companies are actively investigating this technology as a way to deliver same-day packages or regularly send supplies to remote locations without a pilot. These are a real possibility in the next decade.